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Ithemal: Accurate, Portable and Fast Basic Block Throughput Estimation using Deep Neural Networks., , , и . ICML, том 97 из Proceedings of Machine Learning Research, стр. 4505-4515. PMLR, (2019)Making caches work for graph analytics., , , , и . IEEE BigData, стр. 293-302. IEEE Computer Society, (2017)TpuGraphs: A Performance Prediction Dataset on Large Tensor Computational Graphs., , , , , , и . NeurIPS, (2023)Optimizing Cache Performance for Graph Analytics., , , , и . CoRR, (2016)SPADE: A Flexible and Scalable Accelerator for SpMM and SDDMM., , , , , и . ISCA, стр. 19:1-19:15. ACM, (2023)CoMEt: x86 Cost Model Explanation Framework., , , и . CoRR, (2023)COMET: Neural Cost Model Explanation Framework., , , и . MLSys, mlsys.org, (2024)TGOpt: Redundancy-Aware Optimizations for Temporal Graph Attention Networks., и . PPoPP, стр. 354-368. ACM, (2023)All you need is superword-level parallelism: systematic control-flow vectorization with SLP., , и . PLDI, стр. 301-315. ACM, (2022)WACO: Learning Workload-Aware Co-optimization of the Format and Schedule of a Sparse Tensor Program., , , и . ASPLOS (2), стр. 920-934. ACM, (2023)